EDIT · Wan

Wan image model

Image-to-image model designed for controlled restyling, product cleanup, and source-image refinement.

Controlled restyling
Product cleanup
Source-image fidelity

Refine a source image with Wan

Use Wan for controlled restyling, product cleanup, source-image fidelity, and practical image-to-image refinement.

Ratio
4:5
Style
Controlled edit

Opens Studio with Image to Image and Wan preselected.

Wan is a job-specific creative surface

This page is designed around controlled image refinement: a quick generator first, followed by examples, settings, comparison guidance, and trust notes that explain why this model is the right starting point.

Best For

Image-to-image cleanup and controlled restyling.

Watch Out

Not the best first choice when no source image exists.

Alternative

Use Nano Banana Pro for text-to-image campaigns or Qwen Image for brand-system continuity.

What Wan is built to create

Open creation library
controlled image refinement

Product Cleanup

Removes clutter while keeping product identity.

preserve label, clean background, studio light
controlled image refinement

Style Transfer

Applies a new finish without rebuilding the whole image.

same composition, editorial finish, richer shadows
controlled image refinement

Poster Cleanup

Improves a draft poster into a cleaner visual base.

remove artifacts, sharpen subject, keep layout

How to start with Wan

1

Upload the source image and list the preserved elements first.

2

Separate cleanup instructions from style instructions.

3

Use subtle or balanced strength for product identity.

4

Compare variants in the creation library before using them in campaigns.

Edit discipline

Wan is strongest when the user can name exactly what should stay and exactly what should change.

Useful constraints

Preserve composition, preserve product label, remove background clutter, improve light, and keep color family are practical constraints.

Where it fits

Use it for polishing existing assets, cleaning product shots, reworking poster drafts, and producing controlled visual variants.

Trust details that help users create with context

Workflow transparency

The page explains the recommended mode, starting settings, and where a model may need additional iteration before production use.

Human review

Review prompts, people, brands, text, and usage rights before publishing generated assets in campaigns or client work.

Use-case fit

Model guidance is organized by realistic creative jobs such as product motion, story scenes, catalog images, posters, and brand extensions.

Run a first Wan pass instead of only reading docs

This model page helps you decide fit. Once the job is clear, carry the prompt into Studio and generate the first pass.

Why This Converts
Preselects Image to Image
Starts with Wan
Review outputs later in the creations library

What is Wan?

Wan is an Imaveo image model designed for image-to-image cleanup and controlled restyling.

The page is organized around controlled image refinement, with a quick Studio handoff, example gallery, comparison notes, and trust guidance.

How to use Wan on Imaveo

  1. Step 1
    Upload the source image and list the preserved elements first.
  2. Step 2
    Separate cleanup instructions from style instructions.
  3. Step 3
    Use subtle or balanced strength for product identity.
  4. Step 4
    Compare variants in the creation library before using them in campaigns.

When should creators use Wan?

Image-to-image cleanup and controlled restyling.
Edit discipline
Useful constraints
Where it fits

Wan FAQ

Which workflow should Wan start from?
Start from Image to Image; the quick generator passes the model and suggested settings into Studio.
When should I choose a different model instead of Wan?
Not the best first choice when no source image exists.

Continue with related pages